Since I was in high school, I’d always felt overwhelmed by the big concepts that I’d heard from my parents, my peers and the news: “big data”, “cloud computing”, “Internet of Things”…all of which sounded extremely vague, theoretical, and impossible to understand.
As any curious teenager with a little too much free time would do, I decided to delve into learning more about these topics, combing Wikipedia, YouTube videos, and finally an online course on data exploration.
The word “data” is often thrown around as an enigmatic, complex concept that only Facebook scientists or Google engineers can understand. Data is important in nearly every subject, from business to medicine to fashion, but very few actually attempt to understand how to explore data.
For those of us with access to a stable internet connection, quarantine is a great time to utilize the myriad of free online courses available — take a note from Shakira, who’s learning about ancient philosophers through the University of Pennsylvania! If you’re a student, check to see if you have access to services like Coursera and LinkedIn Learning through your school.
Learning to analyze and comprehend data is also one of the most marketable job skills today.
Personally, I’ve been working on completing Yale’s “Financial Markets” and Macquarie University’s “Excel Skills for Business: Essentials” courses on Coursera. Taking a more theoretical course in tandem with a hands-on business course provides me with unique perspectives on data, from tracking stock market movements to creating pivot tables.
So fear the word “data” no more — check out these top-tier online and free courses that can help any beginner immerse themselves in data!
Coursera’s a personal favorite site of mine! Courses and specializations are taught by renowned professors and industry professionals, like the Wharton School’s Barbara E. Kahn and IBM Senior Data Scientist Saeed Aghabozorgi.
Most courses are free anyways, but there’s an added plus if you’re a college student: enroll by July 31st, 2020 to take all courses free through September 30th.
Beginner, 4 hours per week
- This course led by a seasoned team of IBM experts provides an introduction to data science and a chance to work hands-on in the IBM Cloud using real-world data sets.
- Features: Can earn a Professional Certificate, has an Applied Learning Project with room for creativity, can learn basic SQL (a sought-after skill by employers!) and database instances on cloud.
- IBM also has a similar but shorter course with a time of 3 hours/week, “Introduction to Data Science Specialization”
All levels, 13 hours
- This course is led by a University of Michigan Electrical Engineering and Computer Science professor and provides a framework for analyzing the ethics of privacy, consumer information, and big data. It’s great for contextualizing the data you might work with and understand more about data fairness and informed consent, especially in light of recent large scale data breaches!
- Features: A great supplement to a more technical course, perfect for data scientists and beginners alike.
Leetcode is a site typically used for practice coding interviews at companies like Amazon and Google. However, they also have great resources for beginners wanting to get started in both coding and data exploration through courses and even mock coding competitions.
- Created by a Microsoft professional and Leetcode user, this course is an introduction to utilizing arrays, the basis for many data structures. It’s beginner friendly and features code snippets in Java to supplement learning.
- Expertise: Beginner
- Features: Topics begin with articles and culminate in real interview problems to practice on. There’s also an actively monitored discussion forum for questions.
- Developed by a Leetcode Data Scientist, this course explains the oft-mentioned but rarely understood concept of machine learning. It covers the different types of machine learning models, how to build and apply models, and advantages and disadvantages of certain ML algorithms.
- Expertise: All levels
- Features: Leetcode “cards” have both qualitative and quantitative explanations of concepts. Again, there’s an actively monitored discussion forum for questions.
LINKEDIN LEARNING COURSES
Although LinkedIn Learning requires a subscription, I get free access through my university. Try searching for “LinkedIn Learning access” + your college or checking a student services page — it might look something like this. It’s got a ton of videos and courses, with nearly 43,000 results for “data” alone!
Beginner, 1 hour 39 minutes
- I like this course because it delves into how important analytics are: when working with data, it’s super important to understand how to identify, interpret, and summarize data through analytics. Many agree — over 245,288 people have watched this course!
- Features: You’ll learn important skills like creating data dictionaries, pivot charts, and Microsoft Excel tricks. You can also earn a Continuing Education Unit (CEU) certification from the National Association of State Boards of Accountancy (NASBA) after completion.
All levels, 14 hours
This course covers another important tenet of data exploration- mastering SQL, a language used to communicate with databases. It covers essential SQL skills, like creating tables, defining relationships, and manipulating strings.
- Features: Is one of LinkedIn Learning’s “Learning Paths” with lots of modules, like “SQL Essential Training” and “SQL: Data Reporting and Analysis”. You can also earn a certificate of completion that can be added to your LinkedIn!
Beginner, 4 hours 25 minutes
- I think data mining, or the framework for collecting and discovering patterns in data, is one of the most intriguing facets of data science. It combines statistics, AI, and machine learning. This course is a great intro to data mining.
- Expertise: Beginner
- Time: 4 hours, 25 minutes
- Features: Covers data mining foundations, as well as data mining with R and Python.
Similar to LinkedIn Learning and Leetcode, Udemy has instructors teach subjects virtually, from baking to coding. I selected relevant Udemy data courses that were also free.
Udemy also has a wealth of paid courses and even offers a cheaper deal on courses for students.
Beginner, 30 minutes
- This course teaches tips for field data collection with an emphasis on mobile data collection. It would be especially useful for independent researchers looking to optimize data collection.
- Features: You will build a data collection plan, evaluating the risks, costs, technology, and feasibility factors that are difficult to surmise for beginners. If you’re interested in data collection for a personal project or research, this is a good course to start off with.
Intermediate, ~2 hours
- Python is a popular coding language used for data science. This course covers the fundamentals of NumPy, which is Python’s data computing library.
- Features: In addition to an intro to NumPy, a Python introduction is also included for new coders or those looking to brush up on their coding skills. I think this course is great for learning the “scary” parts of coding necessary for data exploration.
Being able to work with data isn’t an exclusive skill for those in the upper echelon of science — through these online courses, it’s easy to start a journey in data science to undertake any project.
The initial course in data exploration I took was a catalyst for my interest in statistics and the intersection of data and other fields, which led to me minoring in Stats and writing for Dashion! For me, online courses helped me access my passions from the comfort of my own home.
Use these resources at your fingertips and newfound free time to learn the valuable skill of understanding data.
June 29, 2020